Eneldo Loza Mencía

Orcid: 0000-0002-2735-9326

Affiliations:
  • TU Darmstadt, Department of Computer Science, Germany


According to our database1, Eneldo Loza Mencía authored at least 60 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Tree-based dynamic classifier chains.
Mach. Learn., November, 2023

Knowledge Graph Embeddings: Open Challenges and Opportunities.
TGDK, 2023

2022
A flexible class of dependence-aware multi-label loss functions.
Mach. Learn., 2022

Comparing Boosting and Bagging for Decision Trees of Rankings.
J. Classif., 2022

2021
Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance.
Frontiers Big Data, 2021

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance.
Comput., 2021

Gradient-Based Label Binning in Multi-label Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Revisiting Non-specific Syndromic Surveillance.
Proceedings of the Advances in Intelligent Data Analysis XIX, 2021

Combining Predictions Under Uncertainty: The Case of Random Decision Trees.
Proceedings of the Discovery Science - 24th International Conference, 2021

Sum-Product Networks for Early Outbreak Detection of Emerging Diseases.
Proceedings of the Artificial Intelligence in Medicine, 2021

2020
Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning.
CoRR, 2020

Rule-Based Multi-label Classification: Challenges and Opportunities.
Proceedings of the Rules and Reasoning - 4th International Joint Conference, 2020

Learning Gradient Boosted Multi-label Classification Rules.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

A Data Set for the Analysis of Text Quality Dimensions in Summarization Evaluation.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Conformal Rule-Based Multi-label Classification.
Proceedings of the KI 2020: Advances in Artificial Intelligence, 2020

On Aggregation in Ensembles of Multilabel Classifiers.
Proceedings of the Discovery Science - 23rd International Conference, 2020

Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains.
Proceedings of the Discovery Science - 23rd International Conference, 2020

2019
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy.
CoRR, 2019

Improving Outbreak Detection with Stacking of Statistical Surveillance Methods.
CoRR, 2019

Learning Context-dependent Label Permutations for Multi-label Classification.
Proceedings of the 36th International Conference on Machine Learning, 2019

On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics.
Proceedings of the Discovery Science - 22nd International Conference, 2019

Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning.
Proceedings of the Discovery Science - 22nd International Conference, 2019

Improving the Fusion of Outbreak Detection Methods with Supervised Learning.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019

2018
Learning Interpretable Rules for Multi-label Classification.
CoRR, 2018

Analysis and Optimization of Deep CounterfactualValue Networks.
CoRR, 2018

What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization.
Proceedings of the Fifth International Conference on Social Networks Analysis, 2018

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Which Scores to Predict in Sentence Regression for Text Summarization?
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Analysis and Optimization of Deep Counterfactual Value Networks.
Proceedings of the KI 2018: Advances in Artificial Intelligence, 2018

Dynamic Classifier Chain with Random Decision Trees.
Proceedings of the Discovery Science - 21st International Conference, 2018

2017
Multi-objective Optimisation-Based Feature Selection for Multi-label Classification.
Proceedings of the Natural Language Processing and Information Systems, 2017

Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction.
Proceedings of the Discovery Science - 20th International Conference, 2017

2016
Learning rules for multi-label classification: a stacking and a separate-and-conquer approach.
Mach. Learn., 2016

A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets.
Inf. Syst., 2016

Medical Concept Embeddings via Labeled Background Corpora.
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

Using semantic similarity for multi-label zero-shot classification of text documents.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

DeepRED - Rule Extraction from Deep Neural Networks.
Proceedings of the Discovery Science - 19th International Conference, 2016

Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization.
Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization.
Proceedings of the COLING 2016, 2016

All-in Text: Learning Document, Label, and Word Representations Jointly.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Simultaneous Feature Selection and Parameter Optimization Using Multi-objective Optimization for Sentiment Analysis.
Proceedings of the 12th International Conference on Natural Language Processing, 2015

2014
Large-Scale Multi-label Text Classification - Revisiting Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Evaluating Multi-label Classification of Incident-related Tweet.
Proceedings of the the 4th Workshop on Making Sense of Microposts co-located with the 23rd International World Wide Web Conference (WWW 2014), 2014

Graded Multilabel Classification by Pairwise Comparisons.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

A Hybrid Multi-strategy Recommender System Using Linked Open Data.
Proceedings of the Semantic Web Evaluation Challenge, 2014

Stacking Label Features for Learning Multilabel Rules.
Proceedings of the Discovery Science - 17th International Conference, 2014

2013
Efficient pairwise multilabel classification.
PhD thesis, 2013

Towards Multilabel Rule Learning.
Proceedings of the LWA 2013. Lernen, 2013

Using Data Mining on Linked Open Data for Analyzing E-Procurement Information - A Machine Learning approach to the Linked Data Mining Challenge 2013.
Proceedings of the International Workshop on Data Mining on Linked Data, 2013

2012
Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

2010
Efficient voting prediction for pairwise multilabel classification.
Neurocomputing, 2010

An Evaluation of Multilabel Classification for the Automatic Annotation of Texts.
Proceedings of the LWA 2010, 2010

Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain.
Proceedings of the Semantic Processing of Legal Texts: Where the Language of Law Meets the Law of Language, 2010

2009
Segmentation of legal documents.
Proceedings of the 12th International Conference on Artificial Intelligence and Law, 2009

2008
Multilabel classification via calibrated label ranking.
Mach. Learn., 2008

Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Pairwise learning of multilabel classifications with perceptrons.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain.
Proceedings of the LWA 2007: Lernen - Wissen, 2007


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